前言

内容大部分参考这篇

文章

。从必应上搜索并下载相应关键词的图片。

获取API

1. 创建一个识别服务账号，这里是
   
   Bing Image Search API
   
   网址。然后点
   
Get API Key

   ，如下图：
   
   
2. 注册或登录如果你有Microsoft 的账户，选择
   
免费试用

   或者
   
送你xx刀

   那个。注册完毕，你会在
   
   You APIs page
   
   这里找到你的APK keys，一般来说有两个。如下图：
   
   

写python代码获取

这里有两种代码，一种是通过命令行输入参数来指定搜索的

图片

和

图片保存路径

，另一种则是在代码里直接指明，这里都给出来

。

• 用命令行输入参数的代码

  # filename: search_ging_api.py
  # import the necessary packages
  from requests import exceptions
  import argparse
  import requests
  import cv2
  import os
  
  # construct the argument parser and parse the arguments
  # parse: 解析器
  '''
  --query: the images search query you're using, which could be anything such as "manhole"
  --output: the output directory for your images.
  '''
  ap = argparse.ArgumentParser()
  ap.add_argument("-q", "--query", required=True,
  	help="search query to search Bing Image API for")
  ap.add_argument("-o", "--output", required=True,
  	help="path to output directory of images")
  args = vars(ap.parse_args())
  
  ##-----------------this part is about global variables -------------------------------------
  # set your Microsoft Cognitive Services API key along with (1) the
  # maximum number of results for a given search and (2) the group size
  # for results (maximum of 50 per request)
  # your API_KEY from Microsoft Azure
  #------------------------------------------------------------
  API_KEY = "这里填你的API_KEY"
  #------------------------------------------------------------
  # You can think of the GROUP_SIZE  parameter as the number of search results to return “per page”.
  # Therefore, if we would like a total of 250 images,
  # we would need to go through 5 “pages” with 50 images “per page”.
  MAX_RESULTS = 250
  GROUP_SIZE = 50
  
  # set the endpoint API URL
  URL = "https://api.cognitive.microsoft.com/bing/v7.0/images/search"
  
  ##----------------------------------------handle exceptions---------------------------
  # when attempting to download images from the web both the Python
  # programming language and the requests library have a number of
  # exceptions that can be thrown so let's build a list of them now
  # so we can filter on them
  EXCEPTIONS = set([IOError, FileNotFoundError,
  	exceptions.RequestException, exceptions.HTTPError,
  	exceptions.ConnectionError, exceptions.Timeout])
  
  
  # store the search term in a convenience variable then set the
  # headers and search parameters
  term = args["query"]
  headers = {"Ocp-Apim-Subscription-Key" : API_KEY}
  params = {"q": term, "offset": 0, "count": GROUP_SIZE}
  
  # make the search
  print("[INFO] searching Bing API for '{}'".format(term))
  search = requests.get(URL, headers=headers, params=params)
  search.raise_for_status()
  
  # grab the results from the search, including the total number of
  # estimated results returned by the Bing API
  results = search.json()
  estNumResults = min(results["totalEstimatedMatches"], MAX_RESULTS)
  print("[INFO] {} total results for '{}'".format(estNumResults,
  	term))
  
  # initialize the total number of images downloaded thus far
  total = 0
  
  # loop over the estimated number of results in `GROUP_SIZE` groups
  for offset in range(0, estNumResults, GROUP_SIZE):
  	# update the search parameters using the current offset, then
  	# make the request to fetch the results
  	print("[INFO] making request for group {}-{} of {}...".format(
  		offset, offset + GROUP_SIZE, estNumResults))
  	params["offset"] = offset
  	search = requests.get(URL, headers=headers, params=params)
  	search.raise_for_status()
  	results = search.json()
  	print("[INFO] saving images for group {}-{} of {}...".format(
  		offset, offset + GROUP_SIZE, estNumResults))
  
  	# loop over the results
  	for v in results["value"]:
  		# try to download the image
  		try:
  			# make a request to download the image
  			print("[INFO] fetching: {}".format(v["contentUrl"]))
  			r = requests.get(v["contentUrl"], timeout=30)
  
  			# build the path to the output image
  			ext = v["contentUrl"][v["contentUrl"].rfind("."):]
  			p = os.path.sep.join([args["output"], "{}{}".format(
  				str(total).zfill(8), ext)])
  
  			# write the image to disk
  			f = open(p, "wb")
  			f.write(r.content)
  			f.close()
  
  		# catch any errors that would not unable us to download the
  		# image
  		except Exception as e:
  			# check to see if our exception is in our list of
  			# exceptions to check for
  			if type(e) in EXCEPTIONS:
  				print("[INFO] skipping: {}".format(v["contentUrl"]))
  				continue
  
  		# try to load the image from disk
  		image = cv2.imread(p)
  
  		# if the image is `None` then we could not properly load the
  		# image from disk (so it should be ignored)
  		if image is None:
  			print("[INFO] deleting: {}".format(p))
  			os.remove(p)
  			continue
  
  		# update the counter
  		total += 1
  

  要注意的是，代码里的
  
API_KEY = "这里填你的API_KEY"

  要填上你自己的API_KEY。
  
  运行的命令是：
  
  
python search_bing_api.py --query "manhole" --output dataset/manhole

  
  其中
  
--query

  后面跟的是你想要搜索的东西名字，
  
--output

  后面就是你的输出目录了。

• 直接在代码指定的

  ### filename: search_bing_api.py
  from requests import exceptions
  import requests
  import cv2
  import os
  import gevent
  
  # poke name to download
  # 你的搜索名字和输出目录
  pokemon = 'mewtwo'
  output = 'datasets/mewtwo'
  
  API_KEY = "你的api"
  MAX_RESULTS = 250
  GROUP_SIZE = 50
  
  # set the endpoint API URL
  URL = "https://api.cognitive.microsoft.com/bing/v7.0/images/search"
  
  # when attempting to download images from the web both the Python
  # programming language and the requests library have a number of
  # exceptions that can be thrown so let's build a list of them now
  # so we can filter on them
  EXCEPTIONS = {IOError, FileNotFoundError, exceptions.RequestException, exceptions.HTTPError, exceptions.ConnectionError,
                exceptions.Timeout}
  
  # store the search term in a convenience variable then set the
  # headers and search parameters
  term = pokemon
  headers = {"Ocp-Apim-Subscription-Key": API_KEY}
  params = {"q": term, "offset": 0, "count": GROUP_SIZE}
  
  # make the search
  print("[INFO] searching Bing API for '{}'".format(term))
  search = requests.get(URL, headers=headers, params=params)
  search.raise_for_status()
  
  # grab the results from the search, including the total number of
  # estimated results returned by the Bing API
  results = search.json()
  estNumResults = min(results["totalEstimatedMatches"], MAX_RESULTS)
  print("[INFO] {} total results for '{}'".format(estNumResults, term))
  
  # initialize the total number of images downloaded thus far
  total = 0
  
  
  def grab_page(url, ext, total):
  
      try:
          # total += 1
          print("[INFO] fetching: {}".format(url))
          r = requests.get(url, timeout=30)
          # build the path to the output image
  
          #here total is only for filename creation
          p = os.path.sep.join([output, "{}{}".format(
              str(total).zfill(8), ext)])
  
          # write the image to disk
          f = open(p, "wb")
          f.write(r.content)
          f.close()
  
          # try to load the image from disk
          image = cv2.imread(p)
  
          # if the image is `None` then we could not properly load the
          # image from disk (so it should be ignored)
          if image is None:
              print("[INFO] deleting: {}".format(p))
              os.remove(p)
              return
  
      # catch any errors that would not unable us to download the
      # image
      except Exception as e:
          # check to see if our exception is in our list of
          # exceptions to check for
          if type(e) in EXCEPTIONS:
              print("[INFO] skipping: {}".format(url))
              return
  
  # loop over the estimated number of results in `GROUP_SIZE` groups
  for offset in range(0, estNumResults, GROUP_SIZE):
      # update the search parameters using the current offset, then
      # make the request to fetch the results
      print("[INFO] making request for group {}-{} of {}...".format(
          offset, offset + GROUP_SIZE, estNumResults))
      params["offset"] = offset
      search = requests.get(URL, headers=headers, params=params)
      search.raise_for_status()
      results = search.json()
      print("[INFO] saving images for group {}-{} of {}...".format(
          offset, offset + GROUP_SIZE, estNumResults))
      # loop over the results
      jobs = []
      for v in results["value"]:
          total += 1
          ext = v["contentUrl"][v["contentUrl"].rfind("."):]
          url = v["contentUrl"]
          
          # create gevent job
          jobs.append(gevent.spawn(grab_page, url, ext, total))
  
      # wait for all jobs to complete
      gevent.joinall(jobs, timeout=10)
      print(total)
  
  

看一下代码，我在上面都注释。

运行，会出来如下结果：